Abstract
The segmentation of medical images poses a great challenge in the area of image processing and analysis due mainly to noise, complex background, fuzzy and overlapping objects, and non-homogeneous gradients. This work uses the so-called locally constrained watershed transform introduced by Beare [1] to address these problems. The shape constraints introduced by this type of flexible watershed transformation permit to successfully segment and separate regions of interest. This type of watershed offers an alternative to other methods (such as distance function flooding) for particle extraction in medical imaging segmentation applications, where particle overlapping is quite common. Cytology images have been used for the experimental results.
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References
Beare, R.: A locally constrained watershed transform. IEEE Transactions on Pattern Analysis and Machine Intelligence 28(7), 1063–1074 (2006), doi:10.1109/TPAMI.2006.132
Duncan, J.S., Ayache, N.: Medical image analysis: Progress over two decades and the challenges ahead. IEEE Transactions on Pattern Analysis and Machine Intelligence 22(1), 85–106 (2000), doi:10.1109/34.824822
Zhang, D., Xiong, H., Zhou, X., Yang, L., Wang, Y.L., Wong, S.: A confident scale–space shape representation framework for cell migration detection. Journal of Microscopy 231(3), 395–407 (2008)
Cseke, I.: A fast segmentation scheme for white blood cell images. In: Kropatsch, W.G., Kampel, M., Hanbury, A. (eds.) Proceedings of the 11th IAPR International Conference on Pattern Recognition. Conference C: Image, Speech and Signal Analysis, vol. 3, pp. 530–533. IBBB, Berlin (1992), doi:10.1109/ICPR.1992.202041
Rojo, M.G., García, G.B., García, J.G., Vicente, M.C.: Preparaciones digitales en los servicios de anatomía patológica (i): Aspectos básicos de imagen digital. Revista Española De Patología 38(2), 69–77 (2005), http://www.pgmacline.es/revpatologia/volumen38/vol38-num2/38-2n02.htm
Rojo, M., Sánchez, F.: El impacto de la historia clínica electrónica en la investigación y la docencia. In (Coordinador), C.J. (ed.): De La Historia Clínica A La Historia De Salud Electrónica. Informes SEIS, vol. 5. SEIS, Pamplona: Sociedad Española de Informática de la Salud, pp. 315–345 Depósito legal: NA-183/2004 (December 2003)
Pablo, C., Lluís, J., Mata, X., Príncep, R., Naranjo, T.: Análisis cuantitativo de técnicas inmunohistoquímicas: Mejora de resultados mediante aplicación de software de análisis de imágenes digitales. In: Congreso Virtual Hispanoamericano de Anatomía Patológica, vol. 7 (October 2005)
Currie, W., Finnegan, D., Hamid, K.: 7. In: Integrating Electronic Health Record, 1st edn., pp. 135–182. Radcliffe Publishing (September 2009)
Grau, V., Mewes, A., Alcaniz, M., Kikinis, R., Warfield, S.: Improved watershed transform for medical image segmentation using prior information. IEEE Transactions on Medical Imaging 23(4), 447–458 (2004)
Klingler Jr., J., Vaughan, C., Fraker Jr., T., Andrews, L.: Segmentation of echocardiographic images using mathematical morphology. IEEE Transactions on Biomedical Engineering 35(11), 925–934 (1988), doi:10.1109/10.8672
Hamarneh, G., Li, X.: Watershed segmentation using prior shape and appearance knowledge. Image and Vision Computing 27(1-2), 59–68 (2009), doi:10.1016/j.imavis.2006.10.009
Murashov, D., Federation, R.: Method for segmentation of low contrast cytological images based on the active contour model. In: Shokin, Y.I., Potaturkin, O.I. (ed.) Automation, Control, and Information Technology. Signal and Image Processing, Novosibirsk, Russia, International Association of Science and Technology for Development, pp. 44–49 (June 2005), Hardcopy ISBN: 0-88986-461-6; CD ISBN: 0-88986-477-2.
Brockett, R.W., Maragos, P.: Evolution equations for continuous-scale morphological filtering. IEEE Transactions on Signal Processing 42(12), 3377–3386 (1994), http://ieeexplore.ieee.org/assets/img/btn.pdf-access-full-text.gif , doi:10.1109/78.340774
McOwen, R.C.: Partial Differential Equations. Tsinghua University Press, Beijing (2004)
Di Rubeto, C., Dempster, A., Khan, S., Jarra, B.: Segmentation of blood images using morphological operators. In: Proceedings of the 15th International Conference on Pattern Recognition, vol. 3, pp. 397–400. IEEE Computer Society, Washington, DC, USA (2000), doi:10.1109/ICPR.2000.903568
Srisang, W.: Segmentation of overlapping chromosome images using computational geometry. Computational Science, Walailak University, Nakhon Si Thammarat, Thailand. Krisanadej Jaroensutasinee, Contributor (December 2008)
Mohana Rao, K., Dempster, A.: Modification on distance transform to avoid over-segmentation and under-segmentation. In: Video/Image Processing and Multimedia Communications 4th EURASIP-IEEE Region 8 International Symposium on VIPromCom, pp. 295–301 (2002)
Beucher, S.: Numerical residues. Image and Vision Computing 25(4), 405–415 (2007) (received September 23, 2005; revised June 26, 2006; accepted July 31, 2006), Available online September 26, 2006, doi:10.1016/j.imavis.2006.07.020
Davies, H.E., Sadler, R.S., Bielsa, S., Maskell, N.A., Rahman, N.M., Davies, R.J.O., Ferry, B.L., Lee, Y.C.: Clinical impact and reliability of pleural fluid mesothelin in undiagnosed pleural effusions. American Journal of Respiratory and Critical Care Medicine 180(5), 437–444 (2009), http://www.biomedsearch.com/nih/Clinical-impact-reliability-pleural-fluid/19299498.html , doi:10.1164/rccm.200811-1729OC
Serra, J.: Image Analysis and Mathematical Morphology, vol. I. Academic Press, London (1982)
Serra, J.: Image Analysis and Mathematical Morphology. Theoretical Advances, vol. II. Academic Press, London (1988)
Soille, P.: Morphological Image Analysis. Springer, Berlin (1999), http://web.ukonline.co.uk/soille
Beucher, S., Meyer, F.: 12. In: The Morphological Approach To Segmentation: The Watershed Transformation, pp. 433–481. Marcel Dekker, New York (1992), http://cmm.ensmp.fr/~beucher/publi/SB_watershed.pdf
Vachier, C., Meyer, F.: The viscous watershed transform. Journal of Mathematical Imaging and Vision 22(2-3), 251–267 (2005), doi:10.1007/s10851-005-4893-3
Beare, R.: Regularized seeded region growing. In: CSIRO Mathematical and Information Sciences, Locked Bag 17, North Ryde, Australia 1670, pp. 91–99. CSIRO Publishing (2002)
Nguyen, H.-T., Worring, M., Van Den Boomgaard, R.: Watersnakes: Energy-driven watershed segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence 25(3), 330–342 (2003), doi:10.1109/TPAMI.2003.1182096
Vargas-Vázquez, D., Crespo, J.L., Maojo, V.: Morphological image reconstruction with criterion from labelled markers. In: Nyström, I., Sanniti di Baja, G., Svensson, S. (eds.) DGCI 2003. LNCS, vol. 2886, pp. 475–484. Springer, Heidelberg (2003), http://www.springerlink.com/content/n22peypd74j409xr/fulltext.pdf
Vargas-Vázquez, D., Crespo, J., Maojo, V., Ríos-Moreno, J.G., Trejo-Perea, M.: Reconstruction with criterion from labeled markers: new approach based on the morphological watershed. Journal of Electronic Imaging 19(4), 043001 (2010), doi:10.1117/1.3491494
Braendle, S.: Watershed algorithms with shape constraints. Master’s thesis, Swiss Federal Institute of Technology - ETH Zurich, Switzerland (April 2008)
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Béliz-Osorio, N., Crespo, J., García-Rojo, M., Muñoz, A., Azpiazu, J. (2011). Cytology Imaging Segmentation Using the Locally Constrained Watershed Transform. In: Soille, P., Pesaresi, M., Ouzounis, G.K. (eds) Mathematical Morphology and Its Applications to Image and Signal Processing. ISMM 2011. Lecture Notes in Computer Science, vol 6671. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21569-8_37
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DOI: https://doi.org/10.1007/978-3-642-21569-8_37
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